v0.2.0

This release introduces the distinction between the Estimator() classes, which provides the .fit(), .update(), .predict() methods and the EstimationMethod() classes, which do the actual fitting of $X$, $y$ to coefficients / weights / betas. This gives

• easier integration of new estimation methods
• easier handling of default parameters for methods
• easier handling of non-default parameters for methods, especially for non-standard parameters like bounds, regularization strengths, etc..
• much cleaner code in OnlineGamlss()

Breaking change: This change gets rid of the estimation_kwargs parameter in OnlineGamlss() which was cumbersome and poorly documented anyways.

Furthermore, we

• align the API of OnlineGamlss() and OnlineLinearModel() and derive the OnlineLasso() from OnlineLinearModel() to show the flexibility of the new approach.
• Introduce a verbosity parameter for OnlineGamlss() to print information to the user.
• Add some properties to (slowly) align more to the sklearn API
• Some minor fixes like fixing #36
• Add a lot of documentation